53 data-"https:"-"https:"-"https:"-"https:"-"https:"-"UCL" research jobs at KINGS COLLEGE LONDON
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conditions. About the role We are seeking a highly motivated postdoctoral Research Associate in research data science and analysis to join Professor Gerome Breen’s internationally recognised team at King’s
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the Centre’s wider ethos of coproduction. Using your experience in quantitative data analysis, you will examine the links between mental distress and work, care and welfare. You will take forward some selected
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data science techniques to model and classify population health risk and disease dynamics at multiple spatial and temporal scales. The PDRA will lead the development of novel approaches for managing
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surveillance, and will contribute to the development of novel approaches for managing confidential spatial health data, including differential privacy and other secure geospatial data protocols. This research
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responsibility is to test key assumptions about differential disease risk by integrating high-resolution socio-ecological, environmental, and novel health data from individual and population sources. This research
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Technicians, Teaching Fellows and AEP equivalent up to and including grade 7. Visit the Centre for Research Staff Development for more information. About You To be successful in this role, we are looking
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surveillance, and will contribute to the development of novel approaches for managing confidential spatial health data, including differential privacy and other secure geospatial data protocols. This research
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models. These models will leverage both imaging data and corresponding radiology reports during training to build comprehensive representations that capture the rich, complementary information contained in
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skills, knowledge and experience required can be found in the Job Description document, provided at the bottom of the next page after you click “Apply Now”. This document will provide information of what
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modeling. The role involves developing and implementing computational methods to integrate single-cell and spatial transcriptomics, proteomics, metabolomics, and metallomics data. Using advanced techniques